Modern Data Architectures with Python A practical guide to building and deploying data pipelines, data warehouses

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Posted on 26 Sep 18:31 | by Apple | 0 views

Key Features
Develop modern data skills in emerging technologies
Learn pragmatic design methodologies like Data Mesh and Lake House
Grow a deeper understanding of data governance
Book Description
Data Architecture with Python will teach you how to integrate your machine learning and data science work streams into your data platform. You will also learn how to take your data and build open lakehouses that can combine with any technology. This book will give you deep hands-on experience with tools like Kafka, Apache Spark, MongoDB, Neo4J, Delta Lake MLFlow, and SQL Dashboards.
By the end of this journey, you would have amassed a wealth of hands-on and theoretical knowledge to architect your own data ecosystems.
What you will learn
Understand data pattern patterns such as Delta Architecture
Learn key details in Spark Internals and how to increase performance
Discover how to design critical Data diagrams
Explore MLOps with tools like AutoML and MLflow
Learn to build data products in a data mesh
Discover data governance and how to build confidence in your data
Learn how to introduce Data Visualizations and Dashboards into your data practice
Who This Book Is For
This book is great for developers, analytics engineers, and managers looking to further develop a data ecosystem within their organization. Basic Python will be useful but not required, Also, experience with data is useful but not necessary to read and do the labs.
Table of Contents
Modern Data Processing Architectures
Basics of Data Analytics Engineering
Cloud Storage and Processing Concepts
Python Batch and Stream Processing with Spark
Streaming Data with Kafka
Python MLOps
Python and SQL based Visualizations
Integrating CI into your workflow
Data Orchestration
Data Governance
Introduction to Saturn Insurance, Deploying CI and ELT
Data Governance and Dashboards

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